30 citations · 59 across the 20 of their papers we have counts for
6 papers · 1 filter
Simple Transferability Estimation for Regression Tasks
Cuong N. Nguyen, Phong Tran, Lam Si Tung Ho +4
We consider transferability estimation, the problem of estimating how well deep learning models transfer from a source to a target task. We focus on regression tasks, which receive…
Generalization Bounds for Deep Transfer Learning Using Majority Predictor Accuracy
Cuong N. Nguyen, Lam Si Tung Ho, Vu Dinh +2
We analyze new generalization bounds for deep learning models trained by transfer learning from a source to a target task. Our bounds utilize a quantity called the majority predict…
Searching for Minimal Optimal Neural Networks
Lam Si Tung Ho, Vu Dinh
Large neural network models have high predictive power but may suffer from overfitting if the training set is not large enough. Therefore, it is desirable to select an appropriate…
OASIS: An Active Framework for Set Inversion
Binh T. Nguyen, Duy M. Nguyen, Lam Si Tung Ho +1
In this work, we introduce a novel method for solving the set inversion problem by formulating it as a binary classification problem. Aiming to develop a fast algorithm that can wo…
Consistent Feature Selection for Analytic Deep Neural Networks
Vu Dinh, Lam Si Tung Ho
One of the most important steps toward interpretability and explainability of neural network models is feature selection, which aims to identify the subset of relevant features. Th…
Bayesian Active Learning With Abstention Feedbacks
Cuong V. Nguyen, Lam Si Tung Ho, Huan Xu +2
We study pool-based active learning with abstention feedbacks where a labeler can abstain from labeling a queried example with some unknown abstention rate. This is an important pr…